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Analytics & Business Process Management July/August 2013
• Digital Edition • e-Newsletter • INFORMS Analytics Society • Analytics Facebook Page
Electoral College put to the math test With the campaign two months behind us and the inauguration of Donald Trump two days away, isn’t it time to put the 2016 U.S. presidential election to bed and focus on issues that have yet to be decided? Of course not.
Eyes on the road: How automated analytics, not dashboards, help you detect significant business incidents
In some circles, business process management (BPM) has developed an unfortunate reputation, particularly among general business media. From the media’s perspective, the negative reputation is implicit in the words themselves: “process” implies rigidity, and “management” implies slowness. Business that’s rigid and slow is antithetical to success in the age of social, mobile and cloud technologies – and it doesn’t address the importance of analytics at all. BPM as a phrase contains everything that may sound bad about old-fashioned enterprise software. The truth is, it is precisely the advent of social, mobile and cloud that makes business process management, when combined with sophisticated data analytics, the cornerstone of success in this new age. The vocabulary of IT is increasingly embracing social, mobile, analytics and cloud – or its catchier acronym “SMAC.” All of these words have one thing in common. They are all ways to engage customers, whether internal or external, to do several important things: to create meaningful interpretations of information, to adapt quickly and nimbly to even small changes in the business environment,
The hype surrounding artificial intelligence (AI) is intense, but for most European businesses surveyed in a recent study by SAS, adoption of AI is still in the early or even planning stages. The good news is, the vast majority of organizations have begun to talk about AI, and a few have even begun to implement suitable projects. There is much optimism about the potential of AI, although fewer were confident that their organization was ready to exploit that potential. Read more Õ
Nearly 40 percent of data professionals spend more than 20 hours per week accessing, blending and preparing data rather than performing actual analysis, according to a survey conducted by TMMData and the Digital Analytics Association. More than 800 DAA community members participated in the survey held earlier this year. The survey revealed that data access, quality and integration present persistent, interrelated roadblocks to efficient and confident analysis across industries. Read more Õ
to improve the customer experience, and most importantly, to do it all more quickly than ever before.
Understanding how analytics works to support intelligent business process and provide peak customer experience means taking a hard look at the two camps of enterprise data-related software.
Digital disruption in the post and parcel industry will see robots and driverless vehicles delivering the mail, augmented reality (AR) creating efficiencies in delivery and artificial intelligence (AI) making it easier to connect customers to products and services, according to new research from Accenture. Read more Õ
The industry analyst firm Forrester and Forrester senior analyst Clay Richardson draw a distinction between “systems of record” and “systems of engagement.” ERP software, big data repositories and other similar technologies comprise what Richardson refers to as systems of record. They record data according to organizational function, and they offer a fairly static representation of a company’s performance – essentially a snapshot, or in the best case, a dashboard. Systems of engagement sit in front of systems of record. They provide the rules for creating customer-facing responses to the data stored in those systems of record. That includes rules for interacting with customers in the mobile, social and cloud environment. The rules themselves are based on an analysis of the information in the systems of record.
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Almost by definition, business process management can be seen as a system of engagement. It’s how workers engage with the people and data they need to make informed business choices, quickly, easily, measurably and routinely. Some BPM systems, it can be argued, still to have one foot in the systems of record camp, simply because they record business rules and processes. At the high end, these systems may even include specific functionality that allows companies to look at their business as a collection of records – essentially a snapshot of information related to particular work transactions. It’s when SMAC enters the picture, though, that the distinction between the two systems emerges. The introduction of methods of engagement such as social, mobile, analytics and cloud, puts a picture frame around Forrester’s contention that BPM is much more than a system of record, and is, in fact, a sophisticated system of engagement. The benefit of this type of analytically supported system of engagement is that it creates routines (business processes) for the best possible customer experience. It is a means to that end, not an end itself. With SMAC, systems of engagement offer businesses a way to make sense of all the means by which workers connect to their business data, their colleagues’ brainpower and their customers.
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Any organization that uses BPM to understand data, create business rules that can be adapted almost on the fly, and apply those rules through various media such as social and mobile technology, is ultimately creating the best possible customer experience it can offer. Everything else is just a delivery mechanism. In particular, social networking – whether accessed through mobile networks or through the cloud – offers a truly meaningful customer experience only when filtered through the lens of analytically supported business processes. Social media without the context of work is nothing more than water cooler talk. It’s the overlap of work with social engagement (call it “worksocial”) that really creates a compelling case for business success. And implicit in the notion of work is the analytical component. The worksocial model applied to data analysis and BPM delivers a modern and more consistent customer experience, increasing organizational productivity and operational efficiency for a more agile business. Real-time analytics can be improved to make informed decisions and take actions from anywhere, at any time. Organizations can quickly respond to new market opportunities, and enterprise social software finally has a real business purpose. Now that we’ve had some background theory of how SMAC relates to analytics and business process, let’s look at what it means in the real world.
For analytics to be actionable, analysis must work in conjunction with process. Business intelligence and analytics yields intelligent business process management. By having more real-time intelligence and analytics directly feeding automated processes via mobile, social and cloud mechanisms, an organization can see trends, issue actions and measure the results through reports delivered by enterprise social media. The application of SMAC to business intelligence and process essentially creates a definition of what a peak customer experience looks like to any one company, all the way up to what someone should do when actually interacting with the customer. Again, keep in mind that both internal and external customers benefit. Following are only a few examples of tangible benefits: Field service management and operational efficiency. One of the largest wind turbine companies in the United States and the world, EDP Renewables has 28 separate, geographically dispersed wind farms each populated with massive 300-foot tall turbine generators. The company’s wind farms generate 3.3 gigawatts of green wind energy – more power than created by the Hoover Dam. The energy market fluctuates greatly. The margin on a watt of energy produced versus a watt sold is constantly in flux, depending on the weather and usage patterns. Identifying areas where the market is very good, such as where demand for climate control is high, might dictate prioritization of that equipment for maintenance. EDP uses this type of real-time streaming data analytics information to help prioritize how the company manages and maintains its wind turbine assets. Weather patterns and related North American weather events are streamed in to the organization’s business process management application as big data information. By analyzing that information in context with data on turbine maintenance issues, EDP can anticipate weather patterns to identify the potential energy output – and the potential price of that energy – for particular farms. This is essential for prioritizing the remediation of turbine issue fixes to maximize the profitability of the company. With thousands of wind turbine components from a variety of vendors, EDP also needs to be able to analyze the relative quality of the turbines and compare their performance over time against the cost to repair and maintain these pieces of equipment. They are constantly reviewing their vendors in this analysis. By correlating factors such as time between repairs from one vendor to another, EDP can make appropriate assessments on the prioritization and maintenance of its equipment. Quality control. A leading global beverage provider uses business analytics in mobile applications to assist in inspecting individual stores for quality control to optimize the customer experience. With tens of thousands of stores all over the world, the company has dramatically accelerated the inspection process and the return of inspection reports that identify areas for improvement. Inspectors in the field are able to perform complete inspections using an iPad, with immediate tabulation of individual store issues, as well as regional and supplier trends. In any given location, field inspectors can examine the store for factors such as equipment and service quality, customer experience, signage and cleanliness. The real-time data crunching that produces scoring data enables inspectors to then sit with store managers and discuss action plans all in the single inspection visit. The company calculates that this process acceleration saves it more than 30,000 hours annually in inspection times, directly improving the quality of the customer experience more rapidly and consistently. Customer satisfaction. Online retail giant Amazon does not source every product they sell. When you purchase something from Amazon, that product may actually be sourced from a departmental store, specialty merchant or other retail organization. When a customer receives an incorrect shipment or an incorrect charge, Amazon refers to this error as a “price purchase variance.” As the intermediary, Amazon is responsible for resolving that variance. Because of the sheer quantity of transactions conducted through its website, Amazon has considerable familiarity and expertise in handling these types of exceptions. In some cases in the past, Amazon would have simply absorbed the difference in cost or the cost of correcting the transaction problem. Price purchase variance settlements were easily costing the company millions of dollars a year. Amazon began developing a process environment that would take in the massive volume of exception handling and apply business rules to it, to automate decision logic. They can see how the variances are coming in, look at the past performance of other vendors, determine the vendors’ track record of fulfilling products and determine whether there is a history of that type of transaction problem. Using statistical analysis of price purchase variance frequency, Amazon now applies business rules to automatically push the issue back to the sourcing vendor and request resolution – whether auto approval, make good or other tasks for the vendors. Through the same system, they can initiate communication with the customers to assure them that they are aware of the problem and are working to resolve it. Social engagement for collaboration. Social media for business involves both external and internal aspects. In consumer social platforms (Twitter, Facebook, LinkedIn, etc.), there clearly can be a business integration element, including brand management and customer relationship management. There’s also an internal component to social media for business. This aspect focuses on developing a project-based social collaboration framework for the open exchange of data and knowledge within the enterprise. In some cases, there may also be a hybrid of external and internal elements. Processes can be designed to read external social media feeds, identify exceptions or trends, and bring those things into an automated environment to set up response mechanisms (particularly important for brand and reputation management). By applying social media in the context of work – the “worksocial” concept mentioned earlier in this article – organizations can openly share both collaborations and conversations related to the analysis at hand. Whether it is an individual case of turbine maintenance, story inspection, invoice exception or any other process, someone else involved in the same type of task can see that information and openly share related data or process recommendations and strategies. This improves business decision-making and the customer experience as well.
Peak customer experience has long been in need of a healthy SMAC. Social, mobile, analytics and cloud capability fuels the ways in which business processes can be automated. Organizations can connect their workers to the job at hand, letting them all make use of whatever information they need to deliver the best result to customers. And SMAC can improve the quality of the user experience at the speed of the Internet, bringing together many users, using many devices, across many different networks, in many different places everywhere, all at once. Malcolm Ross is VP of Product Marketing for Appian. He can be reached at
[email protected].
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